Since 2013, Google has been retooling its robotics program. The New York Times recently reviewed some of the new technology the tech conglomerate has been working on. Google’s researchers are currently focusing on machine learning – one of the hottest topics in collaborative robotics. The article notes that “machine learning – not extravagant new devices – will be the key to developing robotics for manufacturing, warehouse automation, transportation and many other tasks” in the coming years.

At Google’s new lab, two UR5 cobots were being used in their application called TossingBot. The first was equipped with an OnRobot 2-finger electric gripper and was using an overhead camera system and machine learning environment programmed by Google to pick random objects consisting of ping-pong balls, plastic bananas, wood blocks, and other items out of a bin and tossing them several feet across the room into a plastic box held by the other UR5. According to the article, it took about 14 hours of trial and error for the cobot with the gripper to learn from scratch how to locate and throw each of the random items into the plastic bin with 85 percent accuracy. When the program was first started, the cobots did not know how to throw any of the items in the bin. For comparison, researchers laden with the same task had about 80 percent accuracy.

This impressive marriage of physics, cobots, and a style of machine learning that google Google calls “deep learning” could shape the future for companies like Amazon and UPS. The Times notes that “humans sort through items that move in and out of distribution centers. A system like Google’s could automate at least part of the process…” which would certainly lead to faster order placement, faster product delivery, and lower costs for consumers.